/as:drawing-quantity-extract — Count drawing instances

SkillDev tools

Lets your agent count furniture or lighting fixtures on architectural drawings, with page-level evidence for each item.

Available today. Use it from your connected AI after setup.

Add ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.

Then ask your AI: use the /as:drawing-quantity-extract — Count drawing instances skill

About this skill

Extract countable FF&E or luminaire instances from supplied drawings with position-level evidence. Use for plan quantities or symbol counts; not area takeoffs, product specs or cross-source reconciliation.

What this skill tells your AI

The instructions your AI receives, as published by alpacalabsllc/skills-for-architects in skills/drawing-quantity-extract/SKILL.md and read by ahel’s review.

Before acting, read the host contract and declaration (skill:drawing-quantity-extract), using only referenced profiles from the catalog. Requirements do not grant access.

Use the host adapter and available native tools or ordinary task-specific code. Operation names identify semantic procedures, not installed functions. No Arch Studio runner, package installation or executable reconstruction is required. Existing exact authorization persists; ask only for material missing information or permission.

Input: exact supplied drawing files/revisions, building/floor/phase scope and requested tags/types. Output: unadopted instance ledger, scoped counts and coverage/exclusion evidence. No record owner is changed. Read owning instructions for project work; one-off files do not require initialization.

  1. Verify actual source access. Freeze document hashes and physical page list; record printed sheet IDs separately. Keep drawing types/revisions distinct. Missing access calls a real host grant or produces a precise handoff; never substitute another workspace.
  2. Read native evidence procedures. Extract text and coordinates using the native pdf_evidence.extract procedure; use host OCR/visual inspection for image-only labels. Save page-sized checkpoints. A legend index is local to its drawing, not a global type ID.
  3. Build one ledger row per candidate label/symbol at its document/page/bounding box. Classify each as instance, legend, note or unresolved. Count repeated identical tags at distinct positions; inspect duplicate text/OCR layers and overlapping boxes before excluding any. Preserve exclusions and reasons. Associate rooms only using visible boundaries or explicit schedule evidence, not nearest-label proximity.
  4. Inspect each scoped page against the ledger. Reconcile revision callouts and same-page schedules; never count note text as furniture or silently relabel instances because a revision note proposes it. Keep observed label counts and any evidenced revised allocation distinct. If methods disagree, report unresolved counts and the source regions; an approximate number is not verified quantity.
  5. Apply drawing_quantities.summarize with native computation under the complete evidence procedure. It counts supplied classified instances only. Retain the actual result plus the host's per-page coverage and visual evidence; neither a successful command nor unique-tag count proves full extraction.
  6. Return counts by exact tag and scope, source locators, excluded/unresolved instances and pages not inspected. Save only requested derived outputs, fresh-read them and preserve originals. Route comparison with inventories or other drawings to /as:schedule-quantity-reconcile; route adopted record changes to /as:master-schedule, under its authorization. Never certify procurement totals.

Current document placement

Save only authorized derived outputs and verify their actual content, source hashes and complete requested scope. Inline answers and one-off files need no project setup or adoption. For a requested registered project report, resolve confirmed coordinates using the receive-owned native documents.resolve/register semantics in the workspace model, including its complete document/register mutation sequence. Find existing records with documents.query; never guess a folder. This conditional handoff does not authorize schedule or library changes.

Signals

GitHub stars
361
Forks
72
Last commit
Sep 2026
Advanced
Catalog kind
skill
Key
drawing-quantity-extract
Source
github.com/alpacalabsllc/skills-for-architects